New MOOC in Computational Thinking has launched!

By | Educational, Feature, Happenings

The Michigan Institute for Computational Discovery & Engineering and the University of Michigan Center for Academic Innovation have partnered to launch a Massive Open Online Course (MOOC) titled Problem Solving using Computational Thinking. The idea for this MOOC arose from the team’s recognition of the ubiquity of computation. However, the developers were equally keen to distinguish this offering from MOOCs on programming, and to instead highlight how broader computational thinking also makes its presence felt in somewhat unexpected domains. The MOOC is organized in a series of real-world examples that includes how, using computational thinking, it is possible to help plan and prepare for a flu season, track human rights violations or monitor the safety of crowds. The process of computational thinking that this MOOC focuses on ranges from problem identification, through abstraction to evaluating solutions. Problem Solving using Computational Thinking seeks to introduce students and teachers to the systematic thinking needed to conceptualize a problem with the intent of eventually using some computational tools to solve it.

The developers of thisMOOC are drawn from the School of Public Health, the College of Engineering, the School of Education and MICDE. Problem Solving using Computational Thinking is available in Coursera through Michigan Online. To learn more please visit online.umich.edu/courses/problem-solving-using-computational-thinking/.

The NSF Computational Mechanics Vision Workshop

By | Events, Research

Over October 31 and November 1, 2019 MICDE hosted the 2019 Computational Mechanics Vision workshop that aimed to gather and synthesize future directions for computational mechanics research in the United States. Attended by more than 50 experts in various sub-disciplines of computational mechanics from across the country, including five National Science Foundation Program Directors, the group spent a day and a half brainstorming about the future of computational mechanics and defining new paradigms, methodologies and trends in this exciting and vast field. The workshop focused on four emerging areas in Computational Mechanics: Machine Learning, Additive Manufacturing, Computational Medicine, and Risk and Uncertainty Quantification. Operating through open discussions on talks by experts from within and beyond Computational Mechanics, and breakout sessions on the above four topics, the workshop participants arrived at a series of recommendations that could drive NSF’s investments in this field for the next decade and beyond.

To learn more about the event please visit micde.umich.edu/nsf-compmech-workshop-2019/.

46 Peta-FLOPS computation of defects in solid crystals is a finalist in the highest prize for scientific computing

By | HPC, News, Research

From left: Sambit Das, Phani Motamarri and Vikram Gavini

A team led by Prof. Vikram Gavini (Professor of Mechanical Engineering and MICDE affiliate) and including Dr. Sambit Das (MICDE Fellow) and Dr. Phani Motamarri (Assistant Research Scientist and MICDE affiliate), is one of two finalists nominated for this year’s Gordon Bell Prize. The award, generally considered to be the highest honor of its kind, worldwide, recognizes outstanding achievement in high-performance computing. Gavini’s team has developed a methodology that combines advanced finite-element discretization methods for Density Functional Theory (DFT)1 with efficient computational methodologies and mixed precision strategies to achieve a 46 Peta-FLOPS2 sustained performance on 3,800 GPU nodes of the Summit supercomputer. Their work titled “Fast, scalable and accurate finite-element based ab initio calculations using mixed precision computing: 46 PFLOPS simulation of a metallic dislocation3 system” also involved Dr. Bruno Turcksin and Dr. Ying Wai Li from Oak Ridge National Laboratory, and Los Alamos National Laboratory, and Mr. Brent Leback from NVIDIA Corporation.

Electron density contour of pyramidal II screw dislocation system in Mg with 61,640 electrons (6,164 Mg atoms).

First principle calculation methods4 have been immensely successful in predicting a variety of material properties.  These calculations are prohibitively expensive as the computational complexity scales with the number of electrons in the system. Prof. Gavini’s research work is focussed on developing fast and accurate algorithms for Kohn-Sham5 density functional theory, a workhorse of first principle approaches that occupies a significant fraction of the world’s supercomputing resources. In the current work, Dr. Das, Dr. Motamarri and Prof. Gavini used recent developments in the computational framework for real-space DFT calculations using higher-order adaptive finite elements, and pioneered algorithmic advances in the solution of the governing equations, along with a clever parallel implementation that reduced the data access costs and communication bottlenecks. This resulted in fast, accurate and scalable large-scale DFT calculations that are an order of magnitude faster than existing widely used DFT codes. They demonstrated an unprecedented sustained performance of 46 Peta-FLOPS on a dislocation system containing ~100,000 electrons, which is the subject of the Gordon Bell nomination.

Past winners of the Gordon Bell Prize have typically been large teams working on grand challenge problems in astrophysics, climate science, natural hazard modeling, quantum physics, materials science and public health. The purpose of the award is to track the progress over time of parallel computing, with particular emphasis on rewarding innovation in applying high-performance computing to applications in science, engineering, and large-scale data analytics. If you are attending the SuperComputing’19 conference this year in Denver, you can learn more about Dr. Das, Dr. Motamarri and Dr. Gavini’s achievement at the Gordon Bell Prize finalists’ presentations on Wednesday, November 20, 2019, at 4:15 pm in rooms 205-207

Related Publication: S. Das, P. Motamarri, V. Gavini, B. Turcksin, Y. W. Li, and B. Leback. “Fast, Scalable and Accurate Finite-Element Based Ab initio Calculations Using Mixed Precision Computing: 46 PFLOPS Simulation of a Metallic Dislocation System.” To appear in SC’19 Proceedings of the International Conference for High Performance Computing, Networking, Storage, and Analysis, Denver, CO, November 17–22, 2019.

[1] Density functional theory (DFT) is a computational quantum mechanical modeling method used in physics, chemistry and materials science to investigate the electronic structure (or nuclear structure) (principally the ground state) of many-body systems, in particular atoms, molecules, and the condensed phases. https://en.wikipedia.org/wiki/Density_functional_theory.
[2] A PETAFLOP is a unit of computing speed equal to one thousand million million (1015) floating-point operations per second.
[3] In materials science, dislocations are line defects that exist in crystalline solids.
[4] First principle calculation methods use the principle of quantum mechanics to compute properties directly from basic physical quantities such as, e.g., mass and charge.
[5] W. Kohn, L. J. Sham, Self-consistent equations including exchange and correlation effects, Phys. Rev. 140(4A) (1965) A1133.

Research Highlight: Improving aircraft aeropropulsive performance with multidisciplinary design optimization

By | News, Research

Anil Yildirim, Ph.D. Candidate, Aerospace Engineering

MICDE fellow Anil Yildirim, a Ph.D. candidate in the department of Aerospace Engineering, is working towards improving the overall efficiency of commercial tube-and-wing aircraft. The current commercial aircraft design with underwing engines have been the norm since the introduction of the Boeing 707 in the late 50’s [1]. With technological progress in composite materials and electric propulsion, as well as advancement of computational methods and computer power, researchers are developing more energy efficient systems to replace this legacy design. Working with the MDO Lab, lead by Prof. Joaquim R.R.A. Martins, and a team from NASA, Anil is studying the boundary layer ingestion (BLI) system on the STARC–ABL concept, introduced by NASA in 2016 [2] . BLI is an aeropropulsive concept, where a propulsion system is used to ingest the boundary layer generated by the aircraft. This increases propulsive efficiency and reduces the energy dissipated in the wake, effectively improving the overall aeropropulsive performance of the aircraft. Anil and his colleagues in the MDO Lab are using multidisciplinary analysis and optimization tools to study similar technologies, where design intuition is limited and interdisciplinary trades are important. Watch this video to learn more about his work (Authors: Anil Yildirim, Justin S. Gray, Charles A. Mader, Joaquim R. R. A. Martins, DOI: https://doi.org/10.2514/6.2019-3455)

 

[1] “707/720 Commercial Transport: Historical Snapshot,” 2015, http://www.boeing.com/history/
products/707.page
[2] https://ntrs.nasa.gov/archive/nasa/casi.ntrs.nasa.gov/20160007674.pdf

MICDE Director, Krishna Garikipati, wins USACM Fellow award

By | News, Uncategorized

Krishna Garikipati, professor of Mechanical Engineering and of Mathematics, and director of MICDE, has been granted a 2019 United States Association for Computational Mechanics (USACM) Fellows award for his work in developing numerical methods applied to strongly nonlinear problems in living and nonliving material systems.

The Fellows Award recognizes individuals with a distinguished record of research, accomplishment and publication in areas of computational mechanics and demonstrated support of the USACM through membership and participation in the Association, its meetings and activities. All recipients shall be members in good standing of USACM. Multiple awards may be given at two-year intervals.

MICDE to host NSF Computational Mechanics Vision workshop

By | News

In Fall 2019, MICDE will host the NSF workshop entitled Computational Mechanics Vision Workshop. Organized by Boston University, Duke University and the University of Michigan. The workshop’s aim is to solicit and synthesize directions for computational mechanics research and education in the United States over the next decade and beyond from a diverse cross section of scientists and engineers. Read more…

 

Introducing the new Clare Boothe Luce Graduate Fellows at the University of Michigan

By | Feature, News

The Michigan Institute for Computational Discovery and Engineering is pleased to announce the recipients of the Clare Boothe Luce graduate fellowships at the University of Michigan. Jessica Conrad, MS, currently an internee at LLNL, and Elizabeth Livingston, MS, a graduate of the University of Illinois, Urbana-Champaign, will be joining the University of Michigan in the Fall of 2019 to work towards their PhD. They were chosen because of their exceptional academic records and excellent preparation for graduate studies in computational sciences. Elizabeth will join the Mechanical Engineering department in the College of Engineering, and Jessica will join the Applied and Interdisciplinary Mathematics program in the College of Literature, Sciences and the Arts. As required by the fellowship, both students will enroll in the joint PhD in Scientific Computing program.

Elizabeth Livingston, Clare Boothe Luce Fellow at the University of Michigan

Elizabeth Livingston completed a BSc in Engineering Mechanics (with a minor in Computational Science and Engineering) and a MS in Mechanical Engineering at the University of Illinois, Urbana-Champaign. Elizabeth will join Prof. Garikipati’s research group in Mechanical Engineering. Elizabeth will carry out research in computational modeling of biomedical engineering problems. Of particular interest to her is the growth and remodeling of the cardio-vascular system. She will apply cutting-edge techniques of data-driven computational modeling to this topic using principles of scientific computing, including machine learning, uncertainty quantification, and finite element methods.

Elizabeth has a strong academic background, thriving while performing research in fields where women are underrepresented. Her ambition is to become a university faculty member, doing research in computational science. She looks forward to collaborating with colleagues and working with students to help them to succeed as others have helped her.

Jessica Conrad has a BS in mathematics and public health, a master’s in biostatistics, and an excellent track record of computational research both in her training and current work at Los Alamos National Laboratories. This background forms an ideal foundation for blending computing and mathematics in her PhD work, which will enable her to build a successful career in STEM. Jessica’s proposed area of study is in inverse problems in mathematical epidemiology, particularly focused on using computational and mathematical methods to gain useful insights into public health problems. A critical part of this work will include developing computational approaches to parameter identifiability. Conrad plans to work with Prof. Marisa Eisenberg, an expert in identifiability and infectious disease modeling, as one of her two primary co-mentors in the AIM program.

Jessica Conrad, Clare Boothe Luce Fellow at the University of Michigan

The Clare Boothe Luce program is funded by the Henry Luce Foundation. The program was created by Clare Boothe Luce, with the goal of increasing the participation of women in the sciences, mathematics and engineering at every level of higher education. It also serves as a catalyst for colleges and universities to be proactive in their own efforts toward this goal. At the University of Michigan, the program aims to increase women’s participation in the scientific computing community by recruiting top-of-the class women into the PhD in Scientific Computing program. The program is designed to allow the fellows to focus on their academic success by funding their first 3 years in the PhD, freeing them to try high-risk, innovative research projects in a unique interdisciplinary program, with ample networking opportunities and career support.

PhD student opening in Global Ocean Modeling and Scientific Computing

By | Educational, SC2 jobs

A PhD student is sought for a Department of Energy (DOE)-funded project in Global Ocean Modeling and Scientific Computing. The student will work with Professor Brian Arbic at the University of Michigan (U-M), Dr. Phillip Wolfram and Dr. Andrew Roberts of DOE’s Los Alamos National Laboratory, and other DOE scientists. The student will be admitted to the PhD program of the Department of Earth and Environmental Sciences, and will attain a joint PhD in U-M’s Program in Scientific Computing.

Project Description

The project involves insertion of tides into the ocean component of the DOE Energy Exascale Earth System Model (E3SM). The ocean component is based upon the Model Prediction Across Scales (MPAS) code, which uses a finite-element mesh to focus attention on coastal regions. With the addition of tidal forcing, the model will be an ideal tool with which to quantify the changes likely to occur in coastal areas over the next 50-100 years. The student will be strongly encouraged to spend significant time in Los Alamos, working alongside DOE scientists. The project is ideal for students who wish to apply the tools of scientific computing to societally relevant problems, in a university-DOE partnership with significant networking and travel opportunities. The project will increase the number of professionals familiar with both oceanography and computational science, an identified need in several federal ocean modeling centers including Los Alamos National Laboratory.

Application Procedure

  • Applicants must have strong quantitative and programming skills. Backgrounds in mathematics, computer science, physics, and related fields will be given highest consideration.
  • The preferred start date is January 1, 2020, but a start date of September 1, 2020 is also possible.
  • Students interested in applying to work with Professor Arbic should email their CV, unofficial transcript and cover letter, combined into a single PDF file to: Arbic-Ocean-Modeling-PhD@umich.edu. Questions about the project may also be sent to this email address.
  • In addition, an application to the PhD program in Earth and Environmental Sciences is required. See the Department website for application information. The application deadline to start in January 2020, is September 15, 2019. The application deadline for Fall 2020 is January 7, 2020.

The University of Michigan is an equal opportunity employer and is supportive of the needs of dual career couples. Women and minorities are encouraged to apply

Postdoctoral Position in in Machine Learning Methods for Computational Physics at U-M

By | General Interest, News, SC2 jobs

Postdoctoral Position

Machine Learning Methods for Computational Physics
University of Michigan
Department of Mechanical Engineering

Applications are invited for a postdoctoral research positions to join the Computational Physics group in mechanical engineering at the University of Michigan to develop machine learning methods for system identification of partial differential equations.

Qualifications

Applicants should have a doctoral degree in engineering or mathematics with a strong focus on computational science. Some combination of a familiarity with numerical methods for PDEs, high performance computing and machine learning would be ideal.

Compensation

Compensation (salary and benefits) will be offered according to University of Michigan.

The position is available immediately but starting date is negotiable. To apply please contact Prof. Krishna Garikipati at krishna@umich.edu

The University of Michigan offers a vibrant computational science community. 

Postdoctoral Position at U-M School of Public Health

By | General Interest, SC2 jobs

Postdoctoral Position

University of Michigan School of Public Health
Departments of Epidemiology and Health Management and Policy

Applications are invited for two two-year postdoctoral research positions to join the NIH-funded Center for the Assessment of the Public Health Impact of Tobacco Regulations, with a multidisciplinary and multi-institutional team of collaborators. The project will conduct analyses of the public health impact of tobacco regulations across a range of tobacco-related conditions and policy outcomes. The interdisciplinary team includes epidemiologists, economists, tobacco scientists, applied mathematicians and statisticians (Rafael Meza, David Mendez, Ken Warner, Nancy Fleischer (University of Michigan), David Levy (Georgetown University), Ted Holford (Yale University)).

Postdoc description and desired qualifications

The postdoc will develop and examine simulation models of tobacco use that explicitly consider multiple tobacco-products and multiple disease outcomes.

Desired areas of expertise include: dynamic and complex systems, parameter estimation, computer programming (familiarity with, R, Python, C++, Matlab), statistical analysis, econometrics and epidemiology modeling.

Experience developing mathematical/simulation models to address problems in public health, epidemiology or health outcomes is a plus.

Applicants should have a doctoral degree in Epidemiology, Health Economics, Econometric, Engineering, Applied Mathematics, Mathematics, Statistics, Operations Research or related field.

Compensation

Compensation (salary and benefits) will be offered according to University of Michigan and NIH guidelines.

The position is available immediately but starting date is negotiable. To apply please submit CV, names of references, and inquiries to Dr Rafael Meza at rmeza@umich.edu

The University of Michigan offers a vibrant mathematical modeling and complex systems community. Modeling expertise expands across departments including Epidemiology, Health Management and Policy, Complex Systems, Ecology and Evolutionary Biology, Mathematics and Statistics. The School of Public Health is renowned for its cutting-edge research on the applications of mathematical modeling in epidemiology and public health.